Maternal and child cytokine relationship in early life is not altered by cytokine gene polymorphisms.

The development of immune responses is influenced by the interaction between environmental and genetic factors. Our previous study showed a close association between maternal and young infant's cytokine responses. The question is how this association evolves over time and the contribution of genetic polymorphisms to this association. Five cytokines in mitogen-stimulated whole blood culture were measured from pregnant mothers and their children aged 2, 5, 12, 24 and 48 months. Cytokine gene polymorphisms were determined in both mothers and children. High production of maternal interleukin (IL)-10, tumour necrosis factor-α (TNF-α) and interferon-γ (IFN-γ) was significantly associated with higher levels of the corresponding cytokines in their children at 2 months (T2), but the association decreased over time. Maternal single-nucleotide polymorphism (SNP) in IFN-γ gene, rs3181032, was found to be associated with child's IFN-γ levels at T2 only, whereas maternal IL-10 rs4579758 and child's TNF-α rs13215091 were associated with child's corresponding cytokines at later ages but not at T2. In the final models including the gene polymorphisms, maternal cytokines were still the strongest determinant of child cytokines. Maternal cytokine during pregnancy, which could be a proxy for child's environmental factors, showed its highest impact at early age, with no or little influence from genetic factors.

Integrating metabolomics profiling measurements across multiple biobanks.

To optimize the quality of large scale mass-spectrometry based metabolomics data obtained from semiquantitative profiling measurements, it is important to use a strategy in which dedicated measurement designs are combined with a strict statistical quality control regime. This assures consistently high-quality results across measurements from individual studies, but semiquantitative data have been so far only comparable for samples measured within the same study. To enable comparability and integration of semiquantitative profiling data from different large scale studies over the time course of years, the measurement and quality control strategy has to be extended. We introduce a strategy to allow the integration of semiquantitative profiling data from different studies. We demonstrate that lipidomics data generated in samples from three different large biobanks acquired in the time course of 3 years can be effectively combined when using an appropriate measurement design and transfer model. This strategy paves the way toward an integrative usage of semiquantitative metabolomics data sets of multiple studies to validate biological findings in another study and/or to increase the statistical power for discovery of biomarkers or pathways by combining studies.

Large scale meta-analysis of urinary C-terminal telopeptide, serum cartilage oligomeric protein and matrix metalloprotease degraded type II collagen and their role in prevalence, incidence and progression of osteoarthritis.

OBJECTIVE: To evaluate the role of three cartilage-derived biomarkers on osteoarthritis (OA): urinary C-terminal telopeptide (uCTX-II), serum cartilage oligomeric protein (sCOMP), and serum MMP degraded type II collagen (sC2M). SUBJECTS AND METHODS: Samples from 3582 individuals from the Rotterdam Study, the Genetics osteoArthritis and Progression (GARP), the Chingford Study and the TwinsUK cohort were assayed using enzyme-linked immune sorbent assays. Log10 of concentration levels were correlated with risk of hip, hand and knee OA, hip and knee OA severity and incidence, and progression of knee OA, adjusting for age, gender and body mass index (BMI). Results were meta-analysed to assess overall significance. RESULTS: After adjusting for covariates, sCOMP was associated with knee OA and hip and knee OA incidence. Furthermore, sC2M was associated with knee OA incidence and progression. After adjustment for multiple tests (Bonferroni P < 0.002) only the association between sCOMP and knee OA remained significant (odds ratio (OR) = 3.26 (95%CI 1.63-10.1) P = 0.0008 for each standard deviation (SD) increase in biomarker levels). Levels of uCTX-II were significantly associated with risk of hand, hip and knee OA, progression and incidence of knee OA. A receiver operating characteristics (ROC) analysis showed a consistent improvement in prediction of knee OA progression from an average area under the curve (AUC) is 0.646 for age, sex and BMI alone to an AUC = 0.668 including uCTX-II for prediction. CONCLUSIONS: uCTX-II is the most informative biochemical marker for prediction of OA. Both sCOMP and C2M showed some association with OA, thus indicating that they are descriptive of disease activity.

Genome-wide association scan for five major dimensions of personality.

Personality traits are summarized by five broad dimensions with pervasive influences on major life outcomes, strong links to psychiatric disorders and clear heritable components. To identify genetic variants associated with each of the five dimensions of personality we performed a genome-wide association (GWA) scan of 3972 individuals from a genetically isolated population within Sardinia, Italy. On the basis of the analyses of 362 129 single-nucleotide polymorphisms we found several strong signals within or near genes previously implicated in psychiatric disorders. They include the association of neuroticism with SNAP25 (rs362584, P=5 x 10(-5)), extraversion with BDNF and two cadherin genes (CDH13 and CDH23; Ps<5 x 10(-5)), openness with CNTNAP2 (rs10251794, P=3 x 10(-5)), agreeableness with CLOCK (rs6832769, P=9 x 10(-6)) and conscientiousness with DYRK1A (rs2835731, P=3 x 10(-5)). Effect sizes were small (less than 1% of variance), and most failed to replicate in the follow-up independent samples (N up to 3903), though the association between agreeableness and CLOCK was supported in two of three replication samples (overall P=2 x 10(-5)). We infer that a large number of loci may influence personality traits and disorders, requiring larger sample sizes for the GWA approach to confidently identify associated genetic variants.

Testing the druggable endothelial differentiation gene 2 knee osteoarthritis genetic factor for replication in a wide range of sample collections.

OBJECTIVES: To replicate a previously reported association with osteoarthritis (OA) of the promoter single nucleotide polymorphism (SNP) rs10980705 in the endothelial differentiation gene 2 (EDG2). METHODS: Five collections of samples, four from Europe and one from China, were studied. They included patients with 3 OA phenotypes: 1501 with knee OA, 1497 with hip OA and 376 with generalised OA. A total of 2521 controls were also studied. Allele and genotype frequencies of the rs10980705 SNP were analysed in each individual sample collection and in pooled data. In addition, a meta-analysis to incorporate results from the original Japanese report was performed. RESULTS: The association of the rs10980705 SNP with knee OA was not replicated in any of the five sample collections studied or in their combined analysis (odds ratio (OR) 1.10, 95% CI 0.98 to 1.22; p = 0.10). Meta-analysis of all data, including the original Japanese study, did show association with knee OA (OR 1.15, 95% CI 1.06 to 1.26; p = 0.002) but the effect was accounted for by the Japanese data and was less significant than the original report. No association was found with hip OA or with generalised OA. CONCLUSIONS: The original report of a promising genetic association between a druggable G-protein coupled receptor, EDG2, and knee OA has not been replicated. This lack of replication could be due to a modest effect of the promoter polymorphism that will require even larger studies (the winners curse) although a more pronounced effect in the Asian population vs Europeans cannot be excluded.

A unified approach to modelling linkage to quantitative and qualitative traits.

For quantitative traits with a genetic component, random effects approaches are used to test for linkage at observed marker loci. We propose to use these approaches also for binary outcomes observed in sib pairs derived from a population-based cohort study. In addition to a random effect modelling correlation due to polygenic effect, a random effect is included to model the correlation between siblings due to sharing alleles identical by descent (IBD) at the observed marker locus. A two-step analysis is proposed. Firstly, score statistics are computed to test whether correlation is present in the data. Secondly, random effects models are fitted, yielding heritability estimates. To illustrate the methods, data on the contribution of the COL2A1 gene to various binary and quantitative outcomes including the presence of Heberden's nodes and bone mineral density (BMD) are analysed. For most of the traits studied, the score statistics were significant, indicating the presence of genetic effects. For BMD and for Heberden's nodes, the variance explained by the marker locus was 44% (P = 0.0008) and 15% (P = 0.38) respectively. We conclude that the score statistics can be used as a preliminary data analysis. In more sophisticated analysis, heritabilities can be estimated by fitting random effects models.

Mortality risk in men is associated with a common mutation in the methylene-tetrahydrofolate reductase gene (MTHFR).

An elevated level of homocysteine in plasma is associated with the occurrence of cardiovascular disease. A common ala-to-val mutation in the methylenetetrahydrofolate reductase gene (MTHFR) is associated with an elevated level of plasma homocysteine. We studied the possible detrimental effects of the MTHFR mutation on mortality. Within a population-based study in the city of Leiden, the Netherlands, we first compared the MTHFR genotype distribution among 365 elderly subjects aged 85 years and over born in Leiden, and 250 young subjects aged 18 to 40 years whose families originated from the same geographical region. Second, the complete cohort of 666 subjects aged 85 years and over was followed over a period of 10 years for all-cause and cause-specific mortality and stratified according to MTHFR genotype. The frequency of the MTHFR mutation was significantly lower in the elderly than in the young (0.30 and 0.36, respectively; P = 0.03). The difference in genotype distribution was only present in men. The estimated mortality risk up to 85 years in men carrying the vallval genotype was 3.7 (95% confidence interval (CI), 1.3-10.9). Over the age of 85, mortality in men with the vallval genotype was increased 2.0-fold (95% CI, 1.1-3.9) and appeared to be attributable to cancer rather than cardiovascular causes of death. Among women aged 85 years and over, no deleterious effect of the MTHFR mutation was observed. In conclusion, the MTHFR mutation is associated with increased mortality in men in middle and old age, but not in women.

Genome scanning by two-dimensional DNA typing: the use of repetitive DNA sequences for rapid mapping of genetic traits.

The existence of repetitive DNA sequences offers the possibility to assess the mammalian genome for individual variation in its entirety rather than at one or only a few sites. In order to fully explore the various sets of mammalian repeat sequences for this purpose, analytical tools are required which allow many if not all individual members of sets of repetitive elements to be resolved and identified in terms of location and allelic variation. We have applied and further developed an electrophoretic system, two-dimensional DNA typing, which may fulfill these requirements. The two-dimensional system combines separation of DNA fragments by size in a neutral gel, with separation by sequence composition in a denaturing gradient gel. By hybridization with minisatellite- and simple-sequence core probes and by inter-repeat polymerase chain reaction techniques, it is possible to obtain individual--and even chromosome-specific separation patterns that consist of hundreds of spots. Computerized image analysis and matching of such spot patterns allows the rapid assessment of multiple polymorphisms, spread over the genome, to monitor genetic variability in populations. When coupled to databases of polymorphic DNA markers with a known genomic location, two-dimensional DNA typing can greatly accelerate the mapping of genetic traits in humans, animals, and plants.